An Integrated Flood Risk Assessment Model for Cities Located in the Transitional Zone between Taihang Mountains and North China Plain: A Case Study in Shijiazhuang, Hebei, China

Liu, Qiang; Yang, Hongmao; Liu, Min; Sun, Rui; Jun-hai, Zhang

doi:10.3390/atmos10030104

Cited by 5 publications

(6 citation statements)

References 31 publications

(33 reference statements)

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“…On one hand, historical data about flood disaster are applied to analyze and explore the influence on society and nature. To establish a framework of indicators is a traditional and classical way to perform risk assessment, and the dimensions of hazards, exposure, and vulnerability are usually chosen to develop the framework of indicators (Koks et al 2015;Liu et al 2019a;Tian et al 2019). In terms of the three dimensions (hazards, exposure, and vulnerability), Hoque et al (2019) attempted to change the three dimensions to fit in the specific empirical study, and 14 spatial criteria under dimensions of vulnerability and exposure, hazard, and mitigation capacity were used to quantify the degree of risk.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, the MCDM method has become preferred in disaster assessment and management (Hoque et al 2019;Luu, von Meding, and Mojtahedi 2019). It is comprised of fuzzy theory (He et al 2011;Tian et al 2019), neural network algorithms (Chen et al 2019), information diffusion technique (Li et al 2012;Hao, Yang, and Gao 2014;Liu et al 2019b;Yu et al 2020), Analytic Hierarchy Process (Liu et al 2019a), multivariate statistical analysis (Xu et al 2018), and other tools. Among these algorithms, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is preferred in disaster assessment due to its simplicity and intelligibility.…”

Section: Introductionmentioning

confidence: 99%

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Flood risk assessment using the CV-TOPSIS method for the Belt and Road Initiative: an empirical study of Southeast Asia

Tan

et al. 2020

Ecosyst Health Sustain

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Instruction: The countries along the Belt and Road Initiative remain high exposure and vulnerability to climate extremes. Southeast Asia, a significant part of the Belt and Road Initiative, suffers a lot from flood disasters. This study assessed the flood disaster risk from 1990-2015 in all 11 Southeast Asian countries. A model integrating the coefficient of variation approach and the Technique for Order Preference by Similarity to Ideal Solution method was introduced to analyze the flood disaster data. Considering that populations living in areas where elevation is below 5 m and land area where elevation is below 5 m have reached 11.86% and 3.54% (2015), respectively, the two indicators were opted for to propose new metrics for flood disaster risk assessment. Outcomes: Our findings show that the flood disaster risk in Southeast Asia appeared very high during most of the study period. Indonesia had an extremely high flood disaster risk, followed by Vietnam, whereas Laos, Malaysia, Brunei, and Timor Leste had lower flood risks. The model introduced in this paper is quite simple and easy to understand, providing accessible flood risk information for decision makers. Conclusion:The results we obtained have practical implications for land use and investment activities in Southeast Asia.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Flood risk assessment using the CV-TOPSIS method for the Belt and Road Initiative: an empirical study of Southeast Asia

Tan

et al. 2020

Ecosyst Health Sustain

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“…In terms of case areas, existing studies often focus on coastal cities because urban waterlogging is mainly affected by heavy and continuous rainfall [28]. However, in recent years, many inland cities have experienced frequent waterlogging disasters, which has attracted much attention from researchers [29,30]. In terms of the evaluation method, the risk assessments have changed from qualitative research to quantitative research, including geomorphological methods, hydrological and hydrodynamic modeling, system simulation modeling, scenario simulation analysis, coupling methods based on remote sensing and geographic information systems, statistical analysis based on text, and the index system method [31][32][33][34][35][36][37][38].…”

Section: Urban Waterloggingmentioning

confidence: 99%

An Alternative Risk Assessment Model of Urban Waterlogging: A Case Study of Ningbo City

et al. 2021

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Influenced by climate change, extreme weather events occur frequently, and bring huge impacts to urban areas, including urban waterlogging. Conducting risk assessments of urban waterlogging is a critical step to diagnose problems, improve infrastructure and achieve sustainable development facing extreme weathers. This study takes Ningbo, a typical coastal city in the Yangtze River Delta, as an example to conduct a risk assessment of urban waterlogging with high-resolution remote sensing images and high-precision digital elevation models to further analyze the spatial distribution characteristics of waterlogging risk. Results indicate that waterlogging risk in the city proper of Ningbo is mainly low risk, accounting for 36.9%. The higher-risk and medium-risk areas have the same proportions, accounting for 18.7%. They are followed by the lower-risk and high-risk areas, accounting for 15.5% and 9.6%, respectively. In terms of space, waterlogging risk in the city proper of Ningbo is high in the south and low in the north. The high-risk area is mainly located to the west of Jiangdong district and the middle of Haishu district. The low-risk area is mainly distributed in the north of Jiangbei district. These results are consistent with the historical situation of waterlogging in Ningbo, which prove the effectiveness of the risk assessment model and provide an important reference for the government to prevent and mitigate waterlogging. The optimized risk assessment model is also of importance for waterlogging risk assessments in coastal cities. Based on this model, the waterlogging risk of coastal cities can be quickly assessed, combining with local characteristics, which will help improve the city’s capability of responding to waterlogging disasters and reduce socio-economic loss.

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“…This means that the temporal distribution of precipitation is often assumed to be uniform. For the sake of comprehensiveness, this parameter was taken into account and computed as formulated in Equation (7), based on the time of concentration (t c ) of the catchment.…”

Section: Uniformity Coefficient In the Temporal Distribution Of Precipitationmentioning

confidence: 99%

“…In this sense, a vast array of research focuses on the overlaying of thematic layers to produce hazard maps [6][7][8][9][10][11][12][13]. These studies resort to multi-criteria decision analysis (MCDA), especially in the form of weighted sum techniques, to aggregate a series of factors expected to contribute to flooding, such as the slope, land cover, or precipitation.…”

Section: Introductionmentioning

confidence: 99%

ArcDrain: A GIS Add-In for Automated Determination of Surface Runoff in Urban Catchments

Manchado

Roldán-Valcarce

Jato-Espino

et al. 2021

IJERPH

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Surface runoff determination in urban areas is crucial to facilitate ex ante water planning, especially in the context of climate and land cover changes, which are increasing the frequency of floods, due to a combination of violent storms and increased imperviousness. To this end, the spatial identification of urban areas prone to runoff accumulation is essential, to guarantee effective water management in the future. Under these premises, this work sought to produce a tool for automated determination of urban surface runoff using a geographic information systems (GIS). This tool, which was designed as an ArcGIS add-in called ArcDrain, consists of the discretization of urban areas into subcatchments and the subsequent application of the rational method for runoff depth estimation. The formulation of this method directly depends on land cover type and soil permeability, thereby enabling the identification of areas with a low infiltration capacity. ArcDrain was tested using the city of Santander (northern Spain) as a case study. The results achieved demonstrated the accuracy of the tool for detecting high runoff rates and how the inclusion of mitigation measures in the form of sustainable drainage systems (SuDS) and green infrastructure (GI) can help reduce flood hazards in critical zones.

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An Integrated Flood Risk Assessment Model for Cities Located in the Transitional Zone between Taihang Mountains and North China Plain: A Case Study in Shijiazhuang, Hebei, China

Cited by 5 publications

References 31 publications

Flood risk assessment using the CV-TOPSIS method for the Belt and Road Initiative: an empirical study of Southeast Asia

Flood risk assessment using the CV-TOPSIS method for the Belt and Road Initiative: an empirical study of Southeast Asia

An Alternative Risk Assessment Model of Urban Waterlogging: A Case Study of Ningbo City

ArcDrain: A GIS Add-In for Automated Determination of Surface Runoff in Urban Catchments

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